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AC book-brain-visual-reader

Enhanced BOOK BRAIN for LYGO Havens with visual capability. Use to design and maintain a 3-brain filesystem + memory system that also integrates LEFT/RIGHT brain visual checking (browser, images, screenshots) with text and API data for deeper verification and retrieval. Recommended for agents with visual tools or browser automation; use original book-brain only on non-visual systems.

modbender/skill-library-mcp Agent Skills author: modbender MIT 2 files body ≈ 2 308 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Enhanced BOOK BRAIN for LYGO Havens with visual capability.

As a process C 55/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
98
Quality 40%
88
Run on models
none yet
Process rating
C
55/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Secrets in code secret-high-entropy-token references/book-brain-visual-examples.md:75
      High-entropy token-like string (may be an id, hash or a credential) (test fixture / example file)
      - Contract: 0xe5…eaB
      fixture
    • low Concealment en-hide-from-user SKILL.md:237
      Instruction to hide actions from the user (negated — the text forbids it)
      4. Never silently delete or overwrite existing content.
      negated

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 55/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 20When it triggers. No condition that starts the skill
    • 55Failures and branches. 1 branches
    • 60Steps. 101 steps, 6 vague phrases
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2308 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 386: enough signal without eating the budget
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 101 items
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.